Rise in Use of Digital Mental Health Tools and Technologies in the United States During the COVID-19 Pandemic: Survey Study

Dara H Sorkin, Emily A Janio, Elizabeth V Eikey, Margaret Schneider, Katelyn Davis, Stephen M Schueller, Nicole A Stadnick, Kai Zheng, Martha Neary, David Safani, Dana B Mukamel, Dara H Sorkin, Emily A Janio, Elizabeth V Eikey, Margaret Schneider, Katelyn Davis, Stephen M Schueller, Nicole A Stadnick, Kai Zheng, Martha Neary, David Safani, Dana B Mukamel

Abstract

Background: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically.

Objective: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health.

Methods: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects.

Results: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types.

Conclusions: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy.

Keywords: COVID-19; MTurk; anxiety; depression; digital health; digital technologies; distress; e-mental health; mHealth; mental health; self-management.

Conflict of interest statement

Conflicts of Interest: SMS is a member of the Scientific Advisory Board for Headspace for which he receives compensation.

©Dara H Sorkin, Emily A Janio, Elizabeth V Eikey, Margaret Schneider, Katelyn Davis, Stephen M Schueller, Nicole A Stadnick, Kai Zheng, Martha Neary, David Safani, Dana B Mukamel. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.04.2021.

References

    1. Xiong J, Lipsitz O, Nasri F, Lui LM, Gill H, Phan L, Chen-Li D, Iacobucci M, Ho R, Majeed A, McIntyre RS. Impact of COVID-19 pandemic on mental health in the general population: A systematic review. J Affect Disord. 2020 Dec 01;277:55–64. doi: 10.1016/j.jad.2020.08.001.
    1. Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. The Lancet Infectious Diseases. 2020 May;20(5):533–534. doi: 10.1016/s1473-3099(20)30120-1.
    1. Moreno C, Wykes T, Galderisi S, Nordentoft M, Crossley N, Jones N, Cannon M, Correll CU, Byrne L, Carr S, Chen EYH, Gorwood P, Johnson S, Kärkkäinen H, Krystal JH, Lee J, Lieberman J, López-Jaramillo C, Männikkö M, Phillips MR, Uchida H, Vieta E, Vita A, Arango C. How mental health care should change as a consequence of the COVID-19 pandemic. The Lancet Psychiatry. 2020 Sep;7(9):813–824. doi: 10.1016/s2215-0366(20)30307-2.
    1. Xiang Y, Yang Y, Li W, Zhang L, Zhang Q, Cheung T, Ng CH. Timely mental health care for the 2019 novel coronavirus outbreak is urgently needed. The Lancet Psychiatry. 2020 Mar;7(3):228–229. doi: 10.1016/s2215-0366(20)30046-8.
    1. Ayers JW, Leas EC, Johnson DC, Poliak A, Althouse BM, Dredze M, Nobles AL. Internet Searches for Acute Anxiety During the Early Stages of the COVID-19 Pandemic. JAMA Intern Med. 2020 Aug 24;180(12):1706. doi: 10.1001/jamainternmed.2020.3305.
    1. Stijelja S, Mishara BL. COVID-19 and Psychological Distress-Changes in Internet Searches for Mental Health Issues in New York During the Pandemic. JAMA Intern Med. 2020 Oct 05;180(12):1703. doi: 10.1001/jamainternmed.2020.3271.
    1. Twenge JM, Joiner TE. U.S. Census Bureau-assessed prevalence of anxiety and depressive symptoms in 2019 and during the 2020 COVID-19 pandemic. Depress Anxiety. 2020 Oct 15;37(10):954–956. doi: 10.1002/da.23077.
    1. Czeisler. Lane RI, Petrosky E, Wiley JF, Christensen A, Njai R, Weaver MD, Robbins R, Facer-Childs ER, Barger LK, Czeisler CA, Howard ME, Rajaratnam SM. Mental Health, Substance Use, and Suicidal Ideation During the COVID-19 Pandemic - United States, June 24-30, 2020. MMWR Morb Mortal Wkly Rep. 2020 Aug 14;69(32):1049–1057. doi: 10.15585/mmwr.mm6932a1. doi: 10.15585/mmwr.mm6932a1.
    1. Ben-Zeev D. The Digital Mental Health Genie Is Out of the Bottle. Psychiatr Serv. 2020 Dec 01;71(12):1212–1213. doi: 10.1176/appi.ps.202000306.
    1. Dores AR, Geraldo A, Carvalho IP, Barbosa F. The Use of New Digital Information and Communication Technologies in Psychological Counseling during the COVID-19 Pandemic. Int J Environ Res Public Health. 2020 Oct 21;17(20):7663. doi: 10.3390/ijerph17207663.
    1. Chew AMK, Ong R, Lei H, Rajendram M, Verma SK, Fung DSS, Leong JJY, Gunasekeran DV. Digital Health Solutions for Mental Health Disorders During COVID-19. Front Psychiatry. 2020 Sep 9;11:582007. doi: 10.3389/fpsyt.2020.582007. doi: 10.3389/fpsyt.2020.582007.
    1. Wind TR, Rijkeboer M, Andersson G, Riper H. The COVID-19 pandemic: The 'black swan' for mental health care and a turning point for e-health. Internet Interv. 2020 Apr;20:100317. doi: 10.1016/j.invent.2020.100317.
    1. Torous J, Jän Myrick K, Rauseo-Ricupero N, Firth J. Digital Mental Health and COVID-19: Using Technology Today to Accelerate the Curve on Access and Quality Tomorrow. JMIR Ment Health. 2020 Mar 26;7(3):e18848. doi: 10.2196/18848.
    1. Muñoz RF. Using evidence-based internet interventions to reduce health disparities worldwide. J Med Internet Res. 2010 Dec 17;12(5):e60. doi: 10.2196/jmir.1463.
    1. Inkster B. Early Warning Signs of a Mental Health Tsunami: A Coordinated Response to Gather Initial Data Insights From Multiple Digital Services Providers. Front Digit Health. 2021 Feb 10;2:578902. doi: 10.3389/fdgth.2020.578902.
    1. Mobile app usage booms during COVID-19, says App Annie. ZDNet. [2021-04-08].
    1. Muoio D. Mental wellness app use, adoption hasn't spiked during COVID-19. Mobihealthnews. [2021-04-08]. .
    1. Chandler J, Rosenzweig C, Moss AJ, Robinson J, Litman L. Online panels in social science research: Expanding sampling methods beyond Mechanical Turk. Behav Res Methods. 2019 Oct 11;51(5):2022–2038. doi: 10.3758/s13428-019-01273-7.
    1. Chandler J, Shapiro D. Conducting Clinical Research Using Crowdsourced Convenience Samples. Annu Rev Clin Psychol. 2016 Mar 28;12(1):53–81. doi: 10.1146/annurev-clinpsy-021815-093623.
    1. Robinson J, Rosenzweig C, Moss AJ, Litman L. Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool. PLoS One. 2019 Dec 16;14(12):e0226394. doi: 10.1371/journal.pone.0226394.
    1. Buhrmester M, Kwang T, Gosling SD. Amazon's Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data? Perspect Psychol Sci. 2011 Jan 03;6(1):3–5. doi: 10.1177/1745691610393980.
    1. Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep;16(9):606–13. doi: 10.1046/j.1525-1497.2001.016009606.x.
    1. Manea L, Gilbody S, McMillan D. Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): a meta-analysis. CMAJ. 2012 Feb 21;184(3):E191–6. doi: 10.1503/cmaj.110829.
    1. Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006 May 22;166(10):1092–7. doi: 10.1001/archinte.166.10.1092.
    1. Dodson J, Saint PN, Thang J, Eikey EV. Depression Management as Lifestyle Management: Exploring Existing Practices and Perceptions Among College Students. iConference 2020: Sustainable Digital Communities; iConference: International Conference on Information; March 23-26, 2020; Boras, Sweden. 2020. pp. 237–255.
    1. United States Census Bureau American Community Survey 5-Year Estimates, Table B01003. 2018. [2020-11-04]. .
    1. Abdi H. The Bonferonni-Šidák Corrections for Multiple Comparisons. In: Salkind N, editor. Encyclopedia of Measurement and Statistics. Thousands Oaks, CA, USA: Sage; 2007. pp. 103–107.
    1. StataCorp Stata: Software for Statistics and Data Science. [2021-04-08].
    1. Holman EA, Thompson RR, Garfin DR, Silver RC. The unfolding COVID-19 pandemic: A probability-based, nationally representative study of mental health in the United States. Sci Adv. 2020 Oct 18;6(42):eabd5390. doi: 10.1126/sciadv.abd5390. doi: 10.1126/sciadv.abd5390.
    1. COVID-19 Digital Mental Health Resources. NYC Well. [2021-04-08].
    1. Mordecai D, Histon T, Neuwirth E, Heisler WS, Kraft A, Bang Y, Franchino K, Taillac C, Nixon JP. How Kaiser Permanente Created a Mental Health and Wellness Digital Ecosystem. NEJM Catalyst. 2021 Jan;2(1):1. doi: 10.1056/CAT.20.0295.
    1. Eschler J, Burgess E, Reddy M, Mohr DC. Emergent Self-Regulation Practices in Technology and Social Media Use of Individuals Living with Depression. CHI '20: Proceedings of the CHI Conference on Human Factors in Computing Systems; CHI '20: CHI Conference on Human Factors in Computing Systems; April, 2020; Honolulu, HI, USA. 2020. pp. 1–13.
    1. O'Reilly M, Dogra N, Hughes J, Reilly P, George R, Whiteman N. Potential of social media in promoting mental health in adolescents. Health Promot Int. 2019 Oct 01;34(5):981–991. doi: 10.1093/heapro/day056.
    1. De Choudhury M, De S. Mental Health Discourse on reddit: Self-Disclosure, Social Support, and Anonymity. Proceedings of the International AAAI Conference on Web and Social Media; Eighth International AAAI Conference on Weblogs and Social Media; June 1-4, 2014; Ann Arbor, MI, USA. 2014.
    1. Burgess ER, Zhang R, Ernala SK, Feuston JL, De Choudhury M, Czerwinski M, Aguilera A, Schueller SM, Reddy MC. Technology ecosystems. Interactions. 2021 Jan;28(1):66–71. doi: 10.1145/3434564.
    1. Gilbert D. Patient Commentary: Online screening for depression-old (paternalistic) wine in new (digital) bottles. BMJ. 2017 Sep 13;358:j4207. doi: 10.1136/bmj.j4207.
    1. Lau N, O'Daffer A, Colt S, Yi-Frazier JP, Palermo TM, McCauley E, Rosenberg AR. Android and iPhone Mobile Apps for Psychosocial Wellness and Stress Management: Systematic Search in App Stores and Literature Review. JMIR mHealth uHealth. 2020 May 22;8(5):e17798. doi: 10.2196/17798.
    1. O'Loughlin K, Neary M, Adkins EC, Schueller SM. Reviewing the data security and privacy policies of mobile apps for depression. Internet Interv. 2019 Mar;15:110–115. doi: 10.1016/j.invent.2018.12.001.
    1. Huckvale K, Torous J, Larsen ME. Assessment of the Data Sharing and Privacy Practices of Smartphone Apps for Depression and Smoking Cessation. JAMA Netw Open. 2019 Apr 05;2(4):e192542. doi: 10.1001/jamanetworkopen.2019.2542.
    1. Neary M, Schueller SM. State of the Field of Mental Health Apps. Cogn Behav Pract. 2018 Nov;25(4):531–537. doi: 10.1016/j.cbpra.2018.01.002.
    1. Leigh S, Ouyang J, Mimnagh C. Effective? Engaging? Secure? Applying the ORCHA-24 framework to evaluate apps for chronic insomnia disorder. Evid Based Ment Health. 2017 Nov 25;20(4):e20–e20. doi: 10.1136/eb-2017-102751.
    1. Torous JB, Chan SR, Gipson SYT, Kim JW, Nguyen T, Luo J, Wang P. A Hierarchical Framework for Evaluation and Informed Decision Making Regarding Smartphone Apps for Clinical Care. Psychiatr Serv. 2018 May 01;69(5):498–500. doi: 10.1176/appi.ps.201700423.
    1. National Advisory Mental Health Council (NAMHC) Workgroup Opportunities and Challenges of Developing Information Technologies on Behavioral and Social Science Clinical Research. [2020-01-06]. .
    1. Wykes T, Schueller S. Why Reviewing Apps Is Not Enough: Transparency for Trust (T4T) Principles of Responsible Health App Marketplaces. J Med Internet Res. 2019 May 02;21(5):e12390. doi: 10.2196/12390.
    1. Cheung JH, Burns DK, Sinclair RR, Sliter M. Amazon Mechanical Turk in Organizational Psychology: An Evaluation and Practical Recommendations. J Bus Psychol. 2016 Jun 29;32(4):347–361. doi: 10.1007/s10869-016-9458-5.
    1. Bol N, Helberger N, Weert JCM. Differences in mobile health app use: A source of new digital inequalities? The Information Society. 2018 Apr 26;34(3):183–193. doi: 10.1080/01972243.2018.1438550.
    1. Schueller SM, Hunter JF, Figueroa C, Aguilera A. Use of Digital Mental Health for Marginalized and Underserved Populations. Curr Treat Options Psych. 2019 Jul 5;6(3):243–255. doi: 10.1007/s40501-019-00181-z.
    1. Ahorsu DK, Lin C, Imani V, Saffari M, Griffiths MD, Pakpour AH. The Fear of COVID-19 Scale: Development and Initial Validation. Int J Ment Health Addiction. 2020 Mar 27;:1. doi: 10.1007/s11469-020-00270-8.
    1. Lee SA. Coronavirus Anxiety Scale: A brief mental health screener for COVID-19 related anxiety. Death Stud. 2020 Apr 16;44(7):393–401. doi: 10.1080/07481187.2020.1748481.
    1. Leenders NYJM, Sherman WM, Nagaraja HN. Comparisons of four methods of estimating physical activity in adult women. Med Sci Sports Exerc. 2000 Jul;32(7):1320–6. doi: 10.1097/00005768-200007000-00021.
    1. Taylor S, Landry CA, Paluszek MM, Fergus TA, McKay D, Asmundson GJ. Development and initial validation of the COVID Stress Scales. J Anxiety Disord. 2020 May;72:102232. doi: 10.1016/j.janxdis.2020.102232.
    1. Chmielewski M, Kucker SC. An MTurk Crisis? Shifts in Data Quality and the Impact on Study Results. Social Psychological and Personality Science. 2019 Oct 10;11(4):464–473. doi: 10.1177/1948550619875149.
    1. Király O, Potenza MN, Stein DJ, King DL, Hodgins DC, Saunders JB, Griffiths MD, Gjoneska B, Billieux J, Brand M, Abbott MW, Chamberlain SR, Corazza O, Burkauskas J, Sales CM, Montag C, Lochner C, Grünblatt E, Wegmann E, Martinotti G, Lee HK, Rumpf H, Castro-Calvo J, Rahimi-Movaghar A, Higuchi S, Menchon JM, Zohar J, Pellegrini L, Walitza S, Fineberg NA, Demetrovics Z. Preventing problematic internet use during the COVID-19 pandemic: Consensus guidance. Compr Psychiatry. 2020 Jul;100:152180. doi: 10.1016/j.comppsych.2020.152180.
    1. Olatunji O, Ayandele O, Ashirudeen D, Olaniru O. “Infodemic” in a pandemic: COVID-19 conspiracy theories in an African country. Soc Health Behav. 2020;3(4):152–157. doi: 10.4103/SHB.SHB_43_20.
    1. Lin M, Cheng Y. Policy actions to alleviate psychosocial impacts of COVID-19 pandemic: Experiences from Taiwan. Soc Health Behav. 2020;3(2):72. doi: 10.4103/shb.shb_18_20.
    1. Rieger M. To wear or not to wear? Factors influencing wearing face masks in Germany during the COVID-19 pandemic. Soc Health Behav. 2020;3(2):50. doi: 10.4103/shb.shb_23_20.
    1. Machimbarrena JM, Calvete E, Fernández-González L, Álvarez-Bardón A, Álvarez-Fernández L, González-Cabrera J. Internet Risks: An Overview of Victimization in Cyberbullying, Cyber Dating Abuse, Sexting, Online Grooming and Problematic Internet Use. Int J Environ Res Public Health. 2018 Nov 05;15(11):2471. doi: 10.3390/ijerph15112471.
    1. Spada MM. An overview of problematic Internet use. Addictive Behaviors. 2014 Jan;39(1):3–6. doi: 10.1016/j.addbeh.2013.09.007.
    1. Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Prevalence of Depression Symptoms in US Adults Before and During the COVID-19 Pandemic. JAMA Netw Open. 2020 Sep 01;3(9):e2019686. doi: 10.1001/jamanetworkopen.2020.19686.
    1. Bueno-Notivol J, Gracia-García P, Olaya B, Lasheras I, López-Antón Raúl, Santabárbara Javier. Prevalence of depression during the COVID-19 outbreak: A meta-analysis of community-based studies. Int J Clin Health Psychol. 2021 Jan;21(1):100196. doi: 10.1016/j.ijchp.2020.07.007.
    1. Gallagher MW, Zvolensky MJ, Long LJ, Rogers AH, Garey L. The Impact of Covid-19 Experiences and Associated Stress on Anxiety, Depression, and Functional Impairment in American Adults. Cognit Ther Res. 2020 Aug 29;44(6):1–9. doi: 10.1007/s10608-020-10143-y.
    1. Ammerman BA, Burke TA, Jacobucci R, McClure K. Preliminary investigation of the association between COVID-19 and suicidal thoughts and behaviors in the U.S. J Psychiatr Res. 2021 Feb;134:32–38. doi: 10.1016/j.jpsychires.2020.12.037.

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